Overview

Brought to you by YData

Dataset statistics

Number of variables	23
Number of observations	7,566
Missing cells	11,580
Missing cells (%)	6.7%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	7.6 MiB
Average record size in memory	1.0 KiB

Variable types

Text	10
Numeric	5
DateTime	1
Categorical	6
Boolean	1

Alerts

`IMD_Decile` is highly overall correlated with `IMD_Rank`	High correlation
`IMD_Rank` is highly overall correlated with `IMD_Decile`	High correlation
`county` is highly overall correlated with `district` and 1 other fields	High correlation
`current_energy_rating` is highly overall correlated with `new_build`	High correlation
`district` is highly overall correlated with `county` and 1 other fields	High correlation
`ladnm` is highly overall correlated with `county` and 1 other fields	High correlation
`new_build` is highly overall correlated with `current_energy_rating`	High correlation
`price` is highly overall correlated with `total_floor_area`	High correlation
`property_type` is highly overall correlated with `tenure`	High correlation
`tenure` is highly overall correlated with `property_type`	High correlation
`total_floor_area` is highly overall correlated with `price`	High correlation
`new_build` is highly imbalanced (71.5%)	Imbalance
`SAON` has 7138 (94.3%) missing values	Missing
`Locality` has 4404 (58.2%) missing values	Missing
`price` is highly skewed (γ1 = 62.25331961)	Skewed
`transaction` has unique values	Unique
`addr_key` has unique values	Unique

Reproduction

Analysis started	2025-10-09 09:38:48.636909
Analysis finished	2025-10-09 09:38:54.183030
Duration	5.55 seconds
Software version	ydata-profiling vv4.17.0
Download configuration	config.json

transaction
Text

Unique

Distinct	7566
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	960.0 KiB

Length

Max length	38
Median length	38
Mean length	38
Min length	38

Characters and Unicode

Total characters	287,508
Distinct characters	19
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	7,566 ?
Unique (%)	100.0%

Sample

1st row	{3DCCB7C9-D19E-5B9D-E063-4704A8C0331E}
2nd row	{3DCCB7CA-8C58-5B9D-E063-4704A8C0331E}
3rd row	{3DCCB7CA-8C30-5B9D-E063-4704A8C0331E}
4th row	{3DCCB7CA-8CCC-5B9D-E063-4704A8C0331E}
5th row	{3DCCB7C9-D364-5B9D-E063-4704A8C0331E}

Value	Count	Frequency (%)
3dccb7c9-d19e-5b9d-e063-4704a8c0331e	1	< 0.1%
3dccb7ca-85c8-5b9d-e063-4704a8c0331e	1	< 0.1%
3dccb7c9-d364-5b9d-e063-4704a8c0331e	1	< 0.1%
3dccb7ca-8d25-5b9d-e063-4704a8c0331e	1	< 0.1%
3dccb7ca-1cf3-5b9d-e063-4704a8c0331e	1	< 0.1%
3dccb7ca-8aef-5b9d-e063-4704a8c0331e	1	< 0.1%
3dccb7ca-8e32-5b9d-e063-4704a8c0331e	1	< 0.1%
3dccb7ca-4bec-5b9d-e063-4704a8c0331e	1	< 0.1%
3dccb7ca-1ddc-5b9d-e063-4704a8c0331e	1	< 0.1%
3dccb7c9-d317-5b9d-e063-4704a8c0331e	1	< 0.1%
Other values (7556)	7556	99.9%

Most occurring characters

Value	Count	Frequency (%)
C	31916	11.1%
3	31869	11.1%
-	30264	10.5%
0	24352	8.5%
D	18068	6.3%
4	17758	6.2%
E	16714	5.8%
B	16605	5.8%
7	16273	5.7%
A	15110	5.3%
Other values (9)	68579	23.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	287508	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
C	31916	11.1%
3	31869	11.1%
-	30264	10.5%
0	24352	8.5%
D	18068	6.3%
4	17758	6.2%
E	16714	5.8%
B	16605	5.8%
7	16273	5.7%
A	15110	5.3%
Other values (9)	68579	23.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	287508	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
C	31916	11.1%
3	31869	11.1%
-	30264	10.5%
0	24352	8.5%
D	18068	6.3%
4	17758	6.2%
E	16714	5.8%
B	16605	5.8%
7	16273	5.7%
A	15110	5.3%
Other values (9)	68579	23.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	287508	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
C	31916	11.1%
3	31869	11.1%
-	30264	10.5%
0	24352	8.5%
D	18068	6.3%
4	17758	6.2%
E	16714	5.8%
B	16605	5.8%
7	16273	5.7%
A	15110	5.3%
Other values (9)	68579	23.9%

price
Real number (ℝ)

High correlation Skewed

Distinct	1192
Distinct (%)	15.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	298859.48

Minimum	10000
Maximum	31000000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	376.3 KiB

Quantile statistics

Minimum	10000
5-th percentile	115000
Q1	190000
median	254999.5
Q3	349995
95-th percentile	610000
Maximum	31000000
Range	30990000
Interquartile range (IQR)	159995

Descriptive statistics

Standard deviation	395259.29
Coefficient of variation (CV)	1.322559
Kurtosis	4813.3379
Mean	298859.48
Median Absolute Deviation (MAD)	74999.5
Skewness	62.25332
Sum	2.2611708 × 10⁹
Variance	1.562299 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
250000	130	1.7%
200000	123	1.6%
220000	117	1.5%
180000	111	1.5%
230000	105	1.4%
210000	97	1.3%
240000	94	1.2%
215000	94	1.2%
190000	94	1.2%
225000	91	1.2%
Other values (1182)	6510	86.0%

Value	Count	Frequency (%)
10000	1	< 0.1%
14820	1	< 0.1%
15000	1	< 0.1%
20000	1	< 0.1%
25000	1	< 0.1%
32500	1	< 0.1%
35000	3	< 0.1%
39565	1	< 0.1%
39600	1	< 0.1%
40000	1	< 0.1%

Value	Count	Frequency (%)
31000000	1	< 0.1%
2800000	1	< 0.1%
2700000	1	< 0.1%
2175000	1	< 0.1%
2000000	1	< 0.1%
1900000	1	< 0.1%
1837500	1	< 0.1%
1800000	1	< 0.1%
1700000	1	< 0.1%
1675000	1	< 0.1%

transfer_date
Date

Distinct	488
Distinct (%)	6.4%
Missing	0
Missing (%)	0.0%
Memory size	376.3 KiB

Minimum	1996-11-29 00:00:00
Maximum	2025-08-29 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

postcode
Text

Distinct	7030
Distinct (%)	92.9%
Missing	0
Missing (%)	0.0%
Memory size	733.9 KiB

Length

Max length	8
Median length	7
Mean length	7.4039122
Min length	6

Characters and Unicode

Total characters	56,018
Distinct characters	35
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	6,617 ?
Unique (%)	87.5%

Sample

1st row	S18 1QH
2nd row	CV4 7PA
3rd row	B44 0JR
4th row	DY4 7NY
5th row	DE7 6GU

Value	Count	Frequency (%)
le67	106	0.7%
st5	102	0.7%
cv6	91	0.6%
le12	89	0.6%
le9	88	0.6%
cv37	87	0.6%
le2	86	0.6%
le10	81	0.5%
le4	78	0.5%
le7	76	0.5%
Other values (3209)	14248	94.2%

Most occurring characters

Value	Count	Frequency (%)
	7566	13.5%
1	3822	6.8%
E	3036	5.4%
B	2625	4.7%
3	2439	4.4%
2	2356	4.2%
D	2290	4.1%
S	2272	4.1%
4	2112	3.8%
L	2078	3.7%
Other values (25)	25422	45.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	56018	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	7566	13.5%
1	3822	6.8%
E	3036	5.4%
B	2625	4.7%
3	2439	4.4%
2	2356	4.2%
D	2290	4.1%
S	2272	4.1%
4	2112	3.8%
L	2078	3.7%
Other values (25)	25422	45.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	56018	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	7566	13.5%
1	3822	6.8%
E	3036	5.4%
B	2625	4.7%
3	2439	4.4%
2	2356	4.2%
D	2290	4.1%
S	2272	4.1%
4	2112	3.8%
L	2078	3.7%
Other values (25)	25422	45.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	56018	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	7566	13.5%
1	3822	6.8%
E	3036	5.4%
B	2625	4.7%
3	2439	4.4%
2	2356	4.2%
D	2290	4.1%
S	2272	4.1%
4	2112	3.8%
L	2078	3.7%
Other values (25)	25422	45.4%

property_type
Categorical

High correlation

Distinct	4
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	686.6 KiB

S	2852
D	2156
T	1882
F	676

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	7,566
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	D
2nd row	D
3rd row	S
4th row	S
5th row	D

Common Values

Value	Count	Frequency (%)
S	2852	37.7%
D	2156	28.5%
T	1882	24.9%
F	676	8.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
s	2852	37.7%
d	2156	28.5%
t	1882	24.9%
f	676	8.9%

Most occurring characters

Value	Count	Frequency (%)
S	2852	37.7%
D	2156	28.5%
T	1882	24.9%
F	676	8.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7566	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
S	2852	37.7%
D	2156	28.5%
T	1882	24.9%
F	676	8.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7566	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
S	2852	37.7%
D	2156	28.5%
T	1882	24.9%
F	676	8.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7566	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
S	2852	37.7%
D	2156	28.5%
T	1882	24.9%
F	676	8.9%

new_build
Boolean

High correlation Imbalance

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	324.5 KiB

False	7191
True	375

Value	Count	Frequency (%)
False	7191	95.0%
True	375	5.0%

tenure
Categorical

High correlation

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	686.6 KiB

F	6726
L	840

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	7,566
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	F
2nd row	F
3rd row	F
4th row	F
5th row	F

Common Values

Value	Count	Frequency (%)
F	6726	88.9%
L	840	11.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
f	6726	88.9%
l	840	11.1%

Most occurring characters

Value	Count	Frequency (%)
F	6726	88.9%
L	840	11.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7566	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
F	6726	88.9%
L	840	11.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7566	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
F	6726	88.9%
L	840	11.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7566	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
F	6726	88.9%
L	840	11.1%

PAON
Text

Distinct	1035
Distinct (%)	13.7%
Missing	0
Missing (%)	0.0%
Memory size	700.6 KiB

Length

Max length	35
Median length	2
Mean length	2.9039122
Min length	1

Characters and Unicode

Total characters	21,971
Distinct characters	41
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	729 ?
Unique (%)	9.6%

Sample

1st row	27
2nd row	1
3rd row	56
4th row	22
5th row	3

Value	Count	Frequency (%)
1	206	2.5%
4	196	2.3%
8	188	2.2%
5	186	2.2%
2	182	2.2%
7	178	2.1%
6	172	2.1%
3	171	2.0%
12	164	2.0%
9	161	1.9%
Other values (1042)	6573	78.5%

Most occurring characters

Value	Count	Frequency (%)
1	2829	12.9%
2	1941	8.8%
3	1532	7.0%
4	1354	6.2%
5	1219	5.5%
6	1037	4.7%
7	936	4.3%
8	907	4.1%
E	893	4.1%
9	833	3.8%
Other values (31)	8490	38.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	21971	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	2829	12.9%
2	1941	8.8%
3	1532	7.0%
4	1354	6.2%
5	1219	5.5%
6	1037	4.7%
7	936	4.3%
8	907	4.1%
E	893	4.1%
9	833	3.8%
Other values (31)	8490	38.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	21971	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	2829	12.9%
2	1941	8.8%
3	1532	7.0%
4	1354	6.2%
5	1219	5.5%
6	1037	4.7%
7	936	4.3%
8	907	4.1%
E	893	4.1%
9	833	3.8%
Other values (31)	8490	38.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	21971	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	2829	12.9%
2	1941	8.8%
3	1532	7.0%
4	1354	6.2%
5	1219	5.5%
6	1037	4.7%
7	936	4.3%
8	907	4.1%
E	893	4.1%
9	833	3.8%
Other values (31)	8490	38.6%

SAON
Text

Missing

Distinct	177
Distinct (%)	41.4%
Missing	7138
Missing (%)	94.3%
Memory size	563.6 KiB

Length

Max length	27
Median length	19
Mean length	6.8668224
Min length	1

Characters and Unicode

Total characters	2,939
Distinct characters	32
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	108 ?
Unique (%)	25.2%

Sample

1st row	APARTMENT 1
2nd row	26
3rd row	306
4th row	APARTMENT 9
5th row	1

Value	Count	Frequency (%)
flat	192	25.5%
apartment	110	14.6%
1	43	5.7%
3	28	3.7%
2	27	3.6%
4	24	3.2%
5	19	2.5%
7	18	2.4%
6	17	2.3%
8	14	1.9%
Other values (107)	260	34.6%

Most occurring characters

Value	Count	Frequency (%)
T	432	14.7%
A	427	14.5%
	324	11.0%
L	201	6.8%
F	194	6.6%
1	174	5.9%
E	138	4.7%
R	123	4.2%
N	116	3.9%
2	114	3.9%
Other values (22)	696	23.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2939	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
T	432	14.7%
A	427	14.5%
	324	11.0%
L	201	6.8%
F	194	6.6%
1	174	5.9%
E	138	4.7%
R	123	4.2%
N	116	3.9%
2	114	3.9%
Other values (22)	696	23.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2939	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
T	432	14.7%
A	427	14.5%
	324	11.0%
L	201	6.8%
F	194	6.6%
1	174	5.9%
E	138	4.7%
R	123	4.2%
N	116	3.9%
2	114	3.9%
Other values (22)	696	23.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2939	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
T	432	14.7%
A	427	14.5%
	324	11.0%
L	201	6.8%
F	194	6.6%
1	174	5.9%
E	138	4.7%
R	123	4.2%
N	116	3.9%
2	114	3.9%
Other values (22)	696	23.7%

Street
Text

Distinct	5682
Distinct (%)	75.5%
Missing	38
Missing (%)	0.5%
Memory size	775.7 KiB

Length

Max length	26
Median length	23
Mean length	13.212806
Min length	4

Characters and Unicode

Total characters	99,466
Distinct characters	28
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4,652 ?
Unique (%)	61.8%

Sample

1st row	HOLBEIN CLOSE
2nd row	THE LAURELS
3rd row	HORNSEY ROAD
4th row	DARBYS WAY
5th row	BEECH LANE

Value	Count	Frequency (%)
road	2388	15.2%
close	881	5.6%
street	677	4.3%
drive	614	3.9%
avenue	586	3.7%
lane	553	3.5%
way	341	2.2%
crescent	223	1.4%
grove	173	1.1%
the	126	0.8%
Other values (4129)	9128	58.2%

Most occurring characters

Value	Count	Frequency (%)
E	12131	12.2%
R	9296	9.3%
A	8572	8.6%
	8162	8.2%
O	8076	8.1%
L	5977	6.0%
D	5634	5.7%
N	5542	5.6%
S	5256	5.3%
T	5066	5.1%
Other values (18)	25754	25.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	99466	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
E	12131	12.2%
R	9296	9.3%
A	8572	8.6%
	8162	8.2%
O	8076	8.1%
L	5977	6.0%
D	5634	5.7%
N	5542	5.6%
S	5256	5.3%
T	5066	5.1%
Other values (18)	25754	25.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	99466	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
E	12131	12.2%
R	9296	9.3%
A	8572	8.6%
	8162	8.2%
O	8076	8.1%
L	5977	6.0%
D	5634	5.7%
N	5542	5.6%
S	5256	5.3%
T	5066	5.1%
Other values (18)	25754	25.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	99466	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
E	12131	12.2%
R	9296	9.3%
A	8572	8.6%
	8162	8.2%
O	8076	8.1%
L	5977	6.0%
D	5634	5.7%
N	5542	5.6%
S	5256	5.3%
T	5066	5.1%
Other values (18)	25754	25.9%

Locality
Text

Missing

Distinct	844
Distinct (%)	26.7%
Missing	4404
Missing (%)	58.2%
Memory size	635.2 KiB

Length

Max length	22
Median length	19
Mean length	9.4408602
Min length	3

Characters and Unicode

Total characters	29,852
Distinct characters	28
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	357 ?
Unique (%)	11.3%

Sample

1st row	WEST HALLAM
2nd row	CHELLASTON
3rd row	NETHERTON
4th row	WELLESBOURNE
5th row	PINXTON

Value	Count	Frequency (%)
shirley	63	1.5%
long	59	1.4%
green	52	1.2%
eaton	51	1.2%
heath	49	1.2%
great	40	1.0%
on	39	0.9%
shepshed	33	0.8%
mickleover	31	0.7%
hill	31	0.7%
Other values (860)	3713	89.2%

Most occurring characters

Value	Count	Frequency (%)
E	3221	10.8%
O	2803	9.4%
L	2434	8.2%
N	2264	7.6%
R	2158	7.2%
T	1928	6.5%
A	1850	6.2%
S	1678	5.6%
H	1434	4.8%
I	1307	4.4%
Other values (18)	8775	29.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	29852	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
E	3221	10.8%
O	2803	9.4%
L	2434	8.2%
N	2264	7.6%
R	2158	7.2%
T	1928	6.5%
A	1850	6.2%
S	1678	5.6%
H	1434	4.8%
I	1307	4.4%
Other values (18)	8775	29.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	29852	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
E	3221	10.8%
O	2803	9.4%
L	2434	8.2%
N	2264	7.6%
R	2158	7.2%
T	1928	6.5%
A	1850	6.2%
S	1678	5.6%
H	1434	4.8%
I	1307	4.4%
Other values (18)	8775	29.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	29852	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
E	3221	10.8%
O	2803	9.4%
L	2434	8.2%
N	2264	7.6%
R	2158	7.2%
T	1928	6.5%
A	1850	6.2%
S	1678	5.6%
H	1434	4.8%
I	1307	4.4%
Other values (18)	8775	29.4%

town_city
Text

Distinct	94
Distinct (%)	1.2%
Missing	0
Missing (%)	0.0%
Memory size	750.9 KiB

Length

Max length	19
Median length	15
Mean length	9.704996
Min length	4

Characters and Unicode

Total characters	73,428
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	< 0.1%

Sample

1st row	DRONFIELD
2nd row	COVENTRY
3rd row	BIRMINGHAM
4th row	TIPTON
5th row	ILKESTON

Value	Count	Frequency (%)
birmingham	789	9.7%
leicester	549	6.7%
stoke-on-trent	370	4.5%
derby	370	4.5%
coventry	360	4.4%
wolverhampton	256	3.1%
chesterfield	218	2.7%
worcester	214	2.6%
solihull	173	2.1%
walsall	169	2.1%
Other values (95)	4683	57.5%

Most occurring characters

Value	Count	Frequency (%)
E	7969	10.9%
R	6467	8.8%
T	6037	8.2%
O	5836	7.9%
N	5073	6.9%
L	4609	6.3%
I	4473	6.1%
A	3569	4.9%
S	3428	4.7%
H	3103	4.2%
Other values (16)	22864	31.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	73428	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
E	7969	10.9%
R	6467	8.8%
T	6037	8.2%
O	5836	7.9%
N	5073	6.9%
L	4609	6.3%
I	4473	6.1%
A	3569	4.9%
S	3428	4.7%
H	3103	4.2%
Other values (16)	22864	31.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	73428	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
E	7969	10.9%
R	6467	8.8%
T	6037	8.2%
O	5836	7.9%
N	5073	6.9%
L	4609	6.3%
I	4473	6.1%
A	3569	4.9%
S	3428	4.7%
H	3103	4.2%
Other values (16)	22864	31.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	73428	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
E	7969	10.9%
R	6467	8.8%
T	6037	8.2%
O	5836	7.9%
N	5073	6.9%
L	4609	6.3%
I	4473	6.1%
A	3569	4.9%
S	3428	4.7%
H	3103	4.2%
Other values (16)	22864	31.1%

district
Categorical

High correlation

Distinct	44
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	764.8 KiB

BIRMINGHAM	763
COVENTRY	317
DUDLEY	296
CITY OF DERBY	252
STOKE-ON-TRENT	242
Other values (39)	5696

Length

Max length	25
Median length	20
Mean length	11.588025
Min length	5

Characters and Unicode

Total characters	87,675
Distinct characters	24
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	NORTH EAST DERBYSHIRE
2nd row	COVENTRY
3rd row	BIRMINGHAM
4th row	SANDWELL
5th row	EREWASH

Common Values

Value	Count	Frequency (%)
BIRMINGHAM	763	10.1%
COVENTRY	317	4.2%
DUDLEY	296	3.9%
CITY OF DERBY	252	3.3%
STOKE-ON-TRENT	242	3.2%
SANDWELL	240	3.2%
SOLIHULL	228	3.0%
CHARNWOOD	228	3.0%
WARWICK	225	3.0%
WALSALL	218	2.9%
Other values (34)	4557	60.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
birmingham	763	7.1%
staffordshire	397	3.7%
and	396	3.7%
north	353	3.3%
derbyshire	321	3.0%
coventry	317	3.0%
dudley	296	2.8%
east	272	2.5%
south	254	2.4%
city	252	2.3%
Other values (47)	7116	66.3%

Most occurring characters

Value	Count	Frequency (%)
E	8218	9.4%
R	7962	9.1%
O	6452	7.4%
A	5827	6.6%
T	5386	6.1%
S	5272	6.0%
N	5077	5.8%
H	5035	5.7%
L	4757	5.4%
I	4614	5.3%
Other values (14)	29075	33.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	87675	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
E	8218	9.4%
R	7962	9.1%
O	6452	7.4%
A	5827	6.6%
T	5386	6.1%
S	5272	6.0%
N	5077	5.8%
H	5035	5.7%
L	4757	5.4%
I	4614	5.3%
Other values (14)	29075	33.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	87675	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
E	8218	9.4%
R	7962	9.1%
O	6452	7.4%
A	5827	6.6%
T	5386	6.1%
S	5272	6.0%
N	5077	5.8%
H	5035	5.7%
L	4757	5.4%
I	4614	5.3%
Other values (14)	29075	33.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	87675	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
E	8218	9.4%
R	7962	9.1%
O	6452	7.4%
A	5827	6.6%
T	5386	6.1%
S	5272	6.0%
N	5077	5.8%
H	5035	5.7%
L	4757	5.4%
I	4614	5.3%
Other values (14)	29075	33.2%

county
Categorical

High correlation

Distinct	9
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	772.8 KiB

WEST MIDLANDS	2276
STAFFORDSHIRE	1056
LEICESTERSHIRE	1021
DERBYSHIRE	980
WARWICKSHIRE	804
Other values (4)	1429

Length

Max length	14
Median length	13
Mean length	12.666799
Min length	9

Characters and Unicode

Total characters	95,837
Distinct characters	20
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	DERBYSHIRE
2nd row	WEST MIDLANDS
3rd row	WEST MIDLANDS
4th row	WEST MIDLANDS
5th row	DERBYSHIRE

Common Values

Value	Count	Frequency (%)
WEST MIDLANDS	2276	30.1%
STAFFORDSHIRE	1056	14.0%
LEICESTERSHIRE	1021	13.5%
DERBYSHIRE	980	13.0%
WARWICKSHIRE	804	10.6%
WORCESTERSHIRE	740	9.8%
CITY OF DERBY	252	3.3%
STOKE-ON-TRENT	242	3.2%
LEICESTER	195	2.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
west	2276	22.0%
midlands	2276	22.0%
staffordshire	1056	10.2%
leicestershire	1021	9.9%
derbyshire	980	9.5%
warwickshire	804	7.8%
worcestershire	740	7.2%
city	252	2.4%
of	252	2.4%
derby	252	2.4%
Other values (2)	437	4.2%

Most occurring characters

Value	Count	Frequency (%)
E	13721	14.3%
S	12407	12.9%
R	10631	11.1%
I	9149	9.5%
D	6840	7.1%
T	6266	6.5%
W	4624	4.8%
H	4601	4.8%
A	4136	4.3%
L	3492	3.6%
Other values (10)	19970	20.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	95837	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
E	13721	14.3%
S	12407	12.9%
R	10631	11.1%
I	9149	9.5%
D	6840	7.1%
T	6266	6.5%
W	4624	4.8%
H	4601	4.8%
A	4136	4.3%
L	3492	3.6%
Other values (10)	19970	20.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	95837	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
E	13721	14.3%
S	12407	12.9%
R	10631	11.1%
I	9149	9.5%
D	6840	7.1%
T	6266	6.5%
W	4624	4.8%
H	4601	4.8%
A	4136	4.3%
L	3492	3.6%
Other values (10)	19970	20.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	95837	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
E	13721	14.3%
S	12407	12.9%
R	10631	11.1%
I	9149	9.5%
D	6840	7.1%
T	6266	6.5%
W	4624	4.8%
H	4601	4.8%
A	4136	4.3%
L	3492	3.6%
Other values (10)	19970	20.8%

lsoa11cd
Text

Distinct	3296
Distinct (%)	43.6%
Missing	0
Missing (%)	0.0%
Memory size	745.7 KiB

Length

Max length	9
Median length	9
Mean length	9
Min length	9

Characters and Unicode

Total characters	68,094
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1,278 ?
Unique (%)	16.9%

Sample

1st row	E01019793
2nd row	E01009665
3rd row	E01009128
4th row	E01009976
5th row	E01019703

Value	Count	Frequency (%)
e01031231	24	0.3%
e01032892	21	0.3%
e01025789	16	0.2%
e01025917	13	0.2%
e01029836	13	0.2%
e01009102	13	0.2%
e01025957	13	0.2%
e01029416	12	0.2%
e01025703	12	0.2%
e01010223	12	0.2%
Other values (3286)	7417	98.0%

Most occurring characters

Value	Count	Frequency (%)
0	19177	28.2%
1	12860	18.9%
E	7566	11.1%
2	5404	7.9%
9	5317	7.8%
3	4531	6.7%
5	3425	5.0%
4	2679	3.9%
8	2415	3.5%
7	2360	3.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	68094	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	19177	28.2%
1	12860	18.9%
E	7566	11.1%
2	5404	7.9%
9	5317	7.8%
3	4531	6.7%
5	3425	5.0%
4	2679	3.9%
8	2415	3.5%
7	2360	3.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	68094	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	19177	28.2%
1	12860	18.9%
E	7566	11.1%
2	5404	7.9%
9	5317	7.8%
3	4531	6.7%
5	3425	5.0%
4	2679	3.9%
8	2415	3.5%
7	2360	3.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	68094	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	19177	28.2%
1	12860	18.9%
E	7566	11.1%
2	5404	7.9%
9	5317	7.8%
3	4531	6.7%
5	3425	5.0%
4	2679	3.9%
8	2415	3.5%
7	2360	3.5%

msoa11nm
Text

Distinct	892
Distinct (%)	11.8%
Missing	0
Missing (%)	0.0%
Memory size	792.4 KiB

Length

Max length	29
Median length	24
Mean length	15.317076
Min length	9

Characters and Unicode

Total characters	115,889
Distinct characters	51
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	23 ?
Unique (%)	0.3%

Sample

1st row	North East Derbyshire 006
2nd row	Coventry 042
3rd row	Birmingham 011
4th row	Sandwell 016
5th row	Erewash 005

Value	Count	Frequency (%)
birmingham	764	4.3%
001	432	2.4%
003	427	2.4%
006	416	2.3%
005	413	2.3%
010	412	2.3%
staffordshire	397	2.2%
and	395	2.2%
009	391	2.2%
008	387	2.2%
Other values (172)	13363	75.1%

Most occurring characters

Value	Count	Frequency (%)
0	11545	10.0%
	10231	8.8%
e	7794	6.7%
r	7705	6.6%
o	6121	5.3%
a	5456	4.7%
t	4780	4.1%
h	4473	3.9%
n	4419	3.8%
i	4359	3.8%
Other values (41)	49006	42.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	115889	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	11545	10.0%
	10231	8.8%
e	7794	6.7%
r	7705	6.6%
o	6121	5.3%
a	5456	4.7%
t	4780	4.1%
h	4473	3.9%
n	4419	3.8%
i	4359	3.8%
Other values (41)	49006	42.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	115889	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	11545	10.0%
	10231	8.8%
e	7794	6.7%
r	7705	6.6%
o	6121	5.3%
a	5456	4.7%
t	4780	4.1%
h	4473	3.9%
n	4419	3.8%
i	4359	3.8%
Other values (41)	49006	42.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	115889	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	11545	10.0%
	10231	8.8%
e	7794	6.7%
r	7705	6.6%
o	6121	5.3%
a	5456	4.7%
t	4780	4.1%
h	4473	3.9%
n	4419	3.8%
i	4359	3.8%
Other values (41)	49006	42.3%

ladnm
Categorical

High correlation

Distinct	44
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	762.8 KiB

Birmingham	764
Coventry	316
Dudley	297
Derby	252
Stoke-on-Trent	240
Other values (39)	5697

Length

Max length	25
Median length	20
Mean length	11.317076
Min length	5

Characters and Unicode

Total characters	85,625
Distinct characters	41
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	North East Derbyshire
2nd row	Coventry
3rd row	Birmingham
4th row	Sandwell
5th row	Erewash

Common Values

Value	Count	Frequency (%)
Birmingham	764	10.1%
Coventry	316	4.2%
Dudley	297	3.9%
Derby	252	3.3%
Stoke-on-Trent	240	3.2%
Sandwell	238	3.1%
Charnwood	230	3.0%
Solihull	228	3.0%
Warwick	225	3.0%
Walsall	219	2.9%
Other values (34)	4557	60.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
birmingham	764	7.5%
staffordshire	397	3.9%
and	395	3.9%
north	353	3.5%
derbyshire	321	3.1%
coventry	316	3.1%
dudley	297	2.9%
east	274	2.7%
south	253	2.5%
derby	252	2.5%
Other values (45)	6609	64.6%

Most occurring characters

Value	Count	Frequency (%)
e	7794	9.1%
r	7705	9.0%
o	6121	7.1%
a	5456	6.4%
t	4780	5.6%
h	4473	5.2%
n	4419	5.2%
i	4359	5.1%
l	4086	4.8%
s	3544	4.1%
Other values (31)	32888	38.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	85625	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	7794	9.1%
r	7705	9.0%
o	6121	7.1%
a	5456	6.4%
t	4780	5.6%
h	4473	5.2%
n	4419	5.2%
i	4359	5.1%
l	4086	4.8%
s	3544	4.1%
Other values (31)	32888	38.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	85625	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	7794	9.1%
r	7705	9.0%
o	6121	7.1%
a	5456	6.4%
t	4780	5.6%
h	4473	5.2%
n	4419	5.2%
i	4359	5.1%
l	4086	4.8%
s	3544	4.1%
Other values (31)	32888	38.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	85625	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	7794	9.1%
r	7705	9.0%
o	6121	7.1%
a	5456	6.4%
t	4780	5.6%
h	4473	5.2%
n	4419	5.2%
i	4359	5.1%
l	4086	4.8%
s	3544	4.1%
Other values (31)	32888	38.4%

IMD_Decile
Real number (ℝ)

High correlation

Distinct	10
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.9413164

Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	376.3 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	4
median	6
Q3	8
95-th percentile	10
Maximum	10
Range	9
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.8111746
Coefficient of variation (CV)	0.47315685
Kurtosis	-1.149525
Mean	5.9413164
Median Absolute Deviation (MAD)	2
Skewness	-0.21349687
Sum	44952
Variance	7.9027025
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
8	995	13.2%
9	924	12.2%
10	841	11.1%
7	778	10.3%
5	757	10.0%
6	756	10.0%
4	708	9.4%
3	628	8.3%
2	604	8.0%
1	575	7.6%

Value	Count	Frequency (%)
1	575	7.6%
2	604	8.0%
3	628	8.3%
4	708	9.4%
5	757	10.0%
6	756	10.0%
7	778	10.3%
8	995	13.2%
9	924	12.2%
10	841	11.1%

Value	Count	Frequency (%)
10	841	11.1%
9	924	12.2%
8	995	13.2%
7	778	10.3%
6	756	10.0%
5	757	10.0%
4	708	9.4%
3	628	8.3%
2	604	8.0%
1	575	7.6%

IMD_Rank
Real number (ℝ)

High correlation

Distinct	3296
Distinct (%)	43.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	17889.175

Minimum	146
Maximum	32825
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	376.3 KiB

Quantile statistics

Minimum	146
5-th percentile	2431
Q1	10273
median	18664
Q3	25910
95-th percentile	31270
Maximum	32825
Range	32679
Interquartile range (IQR)	15637

Descriptive statistics

Standard deviation	9231.5301
Coefficient of variation (CV)	0.51604002
Kurtosis	-1.1541936
Mean	17889.175
Median Absolute Deviation (MAD)	7774
Skewness	-0.20239516
Sum	1.353495 × 10⁸
Variance	85221149
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
13014	24	0.3%
21511	21	0.3%
10733	16	0.2%
28003	13	0.2%
12506	13	0.2%
3019	13	0.2%
13650	13	0.2%
15217	12	0.2%
22998	12	0.2%
10926	12	0.2%
Other values (3286)	7417	98.0%

Value	Count	Frequency (%)
146	1	< 0.1%
178	1	< 0.1%
202	1	< 0.1%
203	2	< 0.1%
206	1	< 0.1%
225	1	< 0.1%
268	1	< 0.1%
295	3	< 0.1%
340	1	< 0.1%
352	5	0.1%

Value	Count	Frequency (%)
32825	1	< 0.1%
32804	3	< 0.1%
32776	4	0.1%
32774	2	< 0.1%
32764	3	< 0.1%
32723	2	< 0.1%
32718	6	0.1%
32690	1	< 0.1%
32677	1	< 0.1%
32650	3	< 0.1%

addr_key
Text

Unique

Distinct	7566
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	870.4 KiB

Length

Max length	66
Median length	60
Mean length	25.871927
Min length	10

Characters and Unicode

Total characters	195,747
Distinct characters	37
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	7,566 ?
Unique (%)	100.0%

Sample

1st row	27 holbein close s18 1qh
2nd row	1 the laurels cv4 7pa
3rd row	56 hornsey road b44 0jr
4th row	22 darbys way dy4 7ny
5th row	3 beech lane de7 6gu

Value	Count	Frequency (%)
road	2390	6.0%
close	881	2.2%
street	677	1.7%
drive	614	1.5%
avenue	586	1.5%
lane	553	1.4%
way	342	0.9%
1	249	0.6%
crescent	223	0.6%
4	220	0.6%
Other values (8100)	33212	83.1%

Most occurring characters

Value	Count	Frequency (%)
	32381	16.5%
e	16198	8.3%
r	11162	5.7%
a	10583	5.4%
o	8841	4.5%
l	8707	4.4%
d	8188	4.2%
s	8000	4.1%
t	7482	3.8%
n	7023	3.6%
Other values (27)	77182	39.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	195747	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	32381	16.5%
e	16198	8.3%
r	11162	5.7%
a	10583	5.4%
o	8841	4.5%
l	8707	4.4%
d	8188	4.2%
s	8000	4.1%
t	7482	3.8%
n	7023	3.6%
Other values (27)	77182	39.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	195747	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	32381	16.5%
e	16198	8.3%
r	11162	5.7%
a	10583	5.4%
o	8841	4.5%
l	8707	4.4%
d	8188	4.2%
s	8000	4.1%
t	7482	3.8%
n	7023	3.6%
Other values (27)	77182	39.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	195747	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	32381	16.5%
e	16198	8.3%
r	11162	5.7%
a	10583	5.4%
o	8841	4.5%
l	8707	4.4%
d	8188	4.2%
s	8000	4.1%
t	7482	3.8%
n	7023	3.6%
Other values (27)	77182	39.4%

current_energy_rating
Categorical

High correlation

Distinct	7
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	686.6 KiB

D	3314
C	1882
E	1043
B	1008
F	212
Other values (2)	107

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	7,566
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	D
2nd row	C
3rd row	E
4th row	D
5th row	D

Common Values

Value	Count	Frequency (%)
D	3314	43.8%
C	1882	24.9%
E	1043	13.8%
B	1008	13.3%
F	212	2.8%
A	70	0.9%
G	37	0.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
d	3314	43.8%
c	1882	24.9%
e	1043	13.8%
b	1008	13.3%
f	212	2.8%
a	70	0.9%
g	37	0.5%

Most occurring characters

Value	Count	Frequency (%)
D	3314	43.8%
C	1882	24.9%
E	1043	13.8%
B	1008	13.3%
F	212	2.8%
A	70	0.9%
G	37	0.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7566	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
D	3314	43.8%
C	1882	24.9%
E	1043	13.8%
B	1008	13.3%
F	212	2.8%
A	70	0.9%
G	37	0.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7566	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
D	3314	43.8%
C	1882	24.9%
E	1043	13.8%
B	1008	13.3%
F	212	2.8%
A	70	0.9%
G	37	0.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7566	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
D	3314	43.8%
C	1882	24.9%
E	1043	13.8%
B	1008	13.3%
F	212	2.8%
A	70	0.9%
G	37	0.5%

total_floor_area
Real number (ℝ)

High correlation

Distinct	1114
Distinct (%)	14.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	95.380055

Minimum	0
Maximum	1345
Zeros	4
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	376.3 KiB

Quantile statistics

Minimum	0
5-th percentile	52
Q1	71.51
median	85.83
Q3	107
95-th percentile	170
Maximum	1345
Range	1345
Interquartile range (IQR)	35.49

Descriptive statistics

Standard deviation	44.282204
Coefficient of variation (CV)	0.46427112
Kurtosis	96.436589
Mean	95.380055
Median Absolute Deviation (MAD)	16.83
Skewness	5.430991
Sum	721645.49
Variance	1960.9136
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
79	147	1.9%
80	140	1.9%
83	139	1.8%
86	134	1.8%
77	129	1.7%
74	127	1.7%
78	123	1.6%
84	122	1.6%
82	119	1.6%
81	116	1.5%
Other values (1104)	6270	82.9%

Value	Count	Frequency (%)
0	4	0.1%
5	1	< 0.1%
12	1	< 0.1%
17	1	< 0.1%
19	1	< 0.1%
26	1	< 0.1%
27	1	< 0.1%
28	1	< 0.1%
30	1	< 0.1%
30.9	1	< 0.1%

Value	Count	Frequency (%)
1345	1	< 0.1%
634	1	< 0.1%
525	1	< 0.1%
495	1	< 0.1%
477	1	< 0.1%
475	1	< 0.1%
455.85	1	< 0.1%
431	1	< 0.1%
413	1	< 0.1%
412	1	< 0.1%

year
Real number (ℝ)

Distinct	13
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2024.733

Minimum	1996
Maximum	2025
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	346.7 KiB

Quantile statistics

Minimum	1996
5-th percentile	2024
Q1	2025
median	2025
Q3	2025
95-th percentile	2025
Maximum	2025
Range	29
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.90242331
Coefficient of variation (CV)	0.0004456999
Kurtosis	327.1455
Mean	2024.733
Median Absolute Deviation (MAD)	0
Skewness	-14.241169
Sum	15319130
Variance	0.81436782
Monotonicity	Increasing

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
2025	6059	80.1%
2024	1334	17.6%
2023	64	0.8%
2022	49	0.6%
2021	34	0.4%
2020	9	0.1%
2015	6	0.1%
2019	4	0.1%
2005	2	< 0.1%
2008	2	< 0.1%
Other values (3)	3	< 0.1%

Value	Count	Frequency (%)
1996	1	< 0.1%
2001	1	< 0.1%
2005	2	< 0.1%
2006	1	< 0.1%
2008	2	< 0.1%
2015	6	0.1%
2019	4	0.1%
2020	9	0.1%
2021	34	0.4%
2022	49	0.6%

Value	Count	Frequency (%)
2025	6059	80.1%
2024	1334	17.6%
2023	64	0.8%
2022	49	0.6%
2021	34	0.4%
2020	9	0.1%
2019	4	0.1%
2015	6	0.1%
2008	2	< 0.1%
2006	1	< 0.1%

Interactions

Correlations

	IMD_Decile	IMD_Rank	county	current_energy_rating	district	ladnm	new_build	price	property_type	tenure	total_floor_area	year
IMD_Decile	1.000	0.995	0.163	0.056	0.219	0.220	0.104	0.449	0.210	0.062	0.208	0.034
IMD_Rank	0.995	1.000	0.163	0.056	0.219	0.220	0.107	0.453	0.210	0.066	0.211	0.036
county	0.163	0.163	1.000	0.066	0.998	0.995	0.107	0.007	0.154	0.124	0.048	0.018
current_energy_rating	0.056	0.056	0.066	1.000	0.107	0.107	0.545	0.000	0.147	0.187	0.052	0.042
district	0.219	0.219	0.998	0.107	1.000	0.996	0.178	0.000	0.191	0.196	0.072	0.000
ladnm	0.220	0.220	0.995	0.107	0.996	1.000	0.177	0.000	0.191	0.196	0.072	0.000
new_build	0.104	0.107	0.107	0.545	0.178	0.177	1.000	0.000	0.141	0.000	0.046	0.169
price	0.449	0.453	0.007	0.000	0.000	0.000	0.000	1.000	0.002	0.000	0.696	-0.010
property_type	0.210	0.210	0.154	0.147	0.191	0.191	0.141	0.002	1.000	0.859	0.223	0.049
tenure	0.062	0.066	0.124	0.187	0.196	0.196	0.000	0.000	0.859	1.000	0.104	0.075
total_floor_area	0.208	0.211	0.048	0.052	0.072	0.072	0.046	0.696	0.223	0.104	1.000	-0.026
year	0.034	0.036	0.018	0.042	0.000	0.000	0.169	-0.010	0.049	0.075	-0.026	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

	transaction	price	transfer_date	postcode	property_type	new_build	tenure	PAON	SAON	Street	Locality	town_city	district	county	lsoa11cd	msoa11nm	ladnm	IMD_Decile	IMD_Rank	addr_key	current_energy_rating	total_floor_area	year
110	{3DCCB7C9-D19E-5B9D-E063-4704A8C0331E}	79000	1996-11-29	S18 1QH	D	N	F	27	NaN	HOLBEIN CLOSE	NaN	DRONFIELD	NORTH EAST DERBYSHIRE	DERBYSHIRE	E01019793	North East Derbyshire 006	North East Derbyshire	10.0	31035.0	27 holbein close s18 1qh	D	156.02	1996
2	{3DCCB7CA-8C58-5B9D-E063-4704A8C0331E}	350000	2001-07-19	CV4 7PA	D	N	F	1	NaN	THE LAURELS	NaN	COVENTRY	COVENTRY	WEST MIDLANDS	E01009665	Coventry 042	Coventry	9.0	29510.0	1 the laurels cv4 7pa	C	354.00	2001
58	{3DCCB7CA-8C30-5B9D-E063-4704A8C0331E}	192000	2005-03-14	B44 0JR	S	N	F	56	NaN	HORNSEY ROAD	NaN	BIRMINGHAM	BIRMINGHAM	WEST MIDLANDS	E01009128	Birmingham 011	Birmingham	1.0	433.0	56 hornsey road b44 0jr	E	76.87	2005
59	{3DCCB7CA-8CCC-5B9D-E063-4704A8C0331E}	170000	2005-05-20	DY4 7NY	S	Y	F	22	NaN	DARBYS WAY	NaN	TIPTON	SANDWELL	WEST MIDLANDS	E01009976	Sandwell 016	Sandwell	7.0	21008.0	22 darbys way dy4 7ny	D	102.00	2005
1	{3DCCB7C9-D364-5B9D-E063-4704A8C0331E}	450000	2006-03-17	DE7 6GU	D	N	F	3	NaN	BEECH LANE	WEST HALLAM	ILKESTON	EREWASH	DERBYSHIRE	E01019703	Erewash 005	Erewash	10.0	29988.0	3 beech lane de7 6gu	D	57.00	2006
172	{3DCCB7CA-8D25-5B9D-E063-4704A8C0331E}	124950	2008-06-11	DY8 3UJ	T	N	F	76	NaN	SOUTH ROAD	NaN	STOURBRIDGE	DUDLEY	WEST MIDLANDS	E01009848	Dudley 038	Dudley	6.0	17668.0	76 south road dy8 3uj	E	60.43	2008
171	{3DCCB7CA-1CF3-5B9D-E063-4704A8C0331E}	270000	2008-06-25	LE5 5JP	D	N	F	55	NaN	ROWSLEY STREET	NaN	LEICESTER	LEICESTER	LEICESTER	E01013762	Leicester 022	Leicester	3.0	7304.0	55 rowsley street le5 5jp	C	34.40	2008
98	{3DCCB7CA-8AEF-5B9D-E063-4704A8C0331E}	285000	2015-03-28	B31 2SQ	S	N	F	12	NaN	KEMSHEAD AVENUE	NaN	BIRMINGHAM	BIRMINGHAM	WEST MIDLANDS	E01009162	Birmingham 124	Birmingham	3.0	8482.0	12 kemshead avenue b31 2sq	D	78.00	2015
100	{3DCCB7CA-8E32-5B9D-E063-4704A8C0331E}	282500	2015-07-18	B97 6AX	S	N	F	26	NaN	MARTON CLOSE	NaN	REDDITCH	REDDITCH	WORCESTERSHIRE	E01032226	Redditch 001	Redditch	8.0	24851.0	26 marton close b97 6ax	B	95.00	2015
72	{3DCCB7CA-4BEC-5B9D-E063-4704A8C0331E}	322500	2015-07-23	ST5 3AF	D	N	F	25	NaN	CLAYTON ROAD	NaN	NEWCASTLE	NEWCASTLE-UNDER-LYME	STAFFORDSHIRE	E01029605	Newcastle-under-Lyme 014	Newcastle-under-Lyme	9.0	27636.0	25 clayton road st5 3af	D	182.88	2015

	transaction	price	transfer_date	postcode	property_type	new_build	tenure	PAON	SAON	Street	Locality	town_city	district	county	lsoa11cd	msoa11nm	ladnm	IMD_Decile	IMD_Rank	addr_key	current_energy_rating	total_floor_area	year
3720	{3DCCB7CA-88A9-5B9D-E063-4704A8C0331E}	88500	2025-08-27	WS3 4AQ	T	N	F	182	NaN	WOLVERHAMPTON ROAD	PELSALL	WALSALL	WALSALL	WEST MIDLANDS	E01010350	Walsall 003	Walsall	6.0	19134.0	182 wolverhampton road ws3 4aq	C	87.0	2025
2609	{3DCCB7CA-881E-5B9D-E063-4704A8C0331E}	120000	2025-08-27	WS1 3PS	T	N	F	25	NaN	BRACE STREET	NaN	WALSALL	WALSALL	WEST MIDLANDS	E01010371	Walsall 030	Walsall	1.0	1053.0	25 brace street ws1 3ps	C	89.0	2025
4699	{3DCCB7CA-8985-5B9D-E063-4704A8C0331E}	250000	2025-08-27	CV3 6DJ	T	N	F	47	NaN	GREGORY AVENUE	NaN	COVENTRY	COVENTRY	WEST MIDLANDS	E01009666	Coventry 041	Coventry	10.0	30010.0	47 gregory avenue cv3 6dj	C	84.0	2025
6084	{3DCCB7CA-4C17-5B9D-E063-4704A8C0331E}	485000	2025-08-27	TF9 2QL	D	N	F	2	NaN	WOODPECKER VIEW	LOGGERHEADS	MARKET DRAYTON	NEWCASTLE-UNDER-LYME	STAFFORDSHIRE	E01029572	Newcastle-under-Lyme 016	Newcastle-under-Lyme	10.0	30493.0	2 woodpecker view tf9 2ql	D	196.0	2025
3914	{3DCCB7CA-8B4F-5B9D-E063-4704A8C0331E}	225000	2025-08-28	B26 3DJ	T	N	F	53	NaN	BICKLEY GROVE	NaN	BIRMINGHAM	BIRMINGHAM	WEST MIDLANDS	E01009315	Birmingham 081	Birmingham	2.0	5991.0	53 bickley grove b26 3dj	D	77.0	2025
5712	{3DCCB7CA-2668-5B9D-E063-4704A8C0331E}	208000	2025-08-28	B13 8JT	F	N	L	52A	FLAT 6	SALISBURY ROAD	MOSELEY	BIRMINGHAM	BIRMINGHAM	WEST MIDLANDS	E01009184	Birmingham 092	Birmingham	3.0	8032.0	52a flat 6 salisbury road b13 8jt	D	78.0	2025
4563	{3DCCB7CA-8BF1-5B9D-E063-4704A8C0331E}	170000	2025-08-28	B13 9PS	F	N	L	14	NaN	AVON DRIVE	MOSELEY	BIRMINGHAM	BIRMINGHAM	WEST MIDLANDS	E01009185	Birmingham 093	Birmingham	5.0	13722.0	14 avon drive b13 9ps	E	72.0	2025
1594	{3DCCB7C9-D2EC-5B9D-E063-4704A8C0331E}	320000	2025-08-28	NG10 1PP	D	N	F	8	NaN	TEWKESBURY ROAD	LONG EATON	NOTTINGHAM	EREWASH	DERBYSHIRE	E01019678	Erewash 014	Erewash	9.0	29253.0	8 tewkesbury road ng10 1pp	C	97.0	2025
4336	{3DCCB7CA-8930-5B9D-E063-4704A8C0331E}	170000	2025-08-28	B36 9TZ	T	N	F	2	NaN	PIKEHORNE CROFT	NaN	BIRMINGHAM	SOLIHULL	WEST MIDLANDS	E01010120	Solihull 001	Solihull	4.0	10097.0	2 pikehorne croft b36 9tz	D	66.0	2025
6680	{3DCCB7CA-4D3F-5B9D-E063-4704A8C0331E}	250000	2025-08-29	ST13 8XF	D	N	F	3	NaN	THE WILLOWS	NaN	LEEK	STAFFORDSHIRE MOORLANDS	STAFFORDSHIRE	E01029816	Staffordshire Moorlands 006	Staffordshire Moorlands	9.0	28838.0	3 the willows st13 8xf	D	56.0	2025

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories